Head of Engineering, Applied AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of Theta’s engineering efforts while leading the data science team, primarily focusing on development.

• Establish the technical vision and assist the team in overcoming challenging delivery obstacles.

• Collaborate with the technical teams of clients.

• Design a reliable execution framework for thousands of models on cloud infrastructure.

• Partner with client engineering teams to package and deploy models within their respective environments.

• Ensure the pipeline from raw client data to validated model outputs is both reliable and reusable.

• Create AI-assisted workflows for data preparation and modeling processes.

• Set benchmarks for testing, validation, and dependable deployment.

• Evaluate the team’s code and design implementations.

• Determine what should be built, automated, or outsourced while maintaining focus on long-term maintainability.

• Assist data scientists in resolving complex client delivery issues and contribute directly when engagements overlap.

⛳️ Requirements

• Strong engineering skills, along with the curiosity and judgment to navigate engineering, data science, and client delivery effectively.

• Experience in building and operating production-grade data or ML systems end-to-end at scale on cloud infrastructure.

• Familiarity with cloud infrastructure; GCP is preferred, but AWS, Azure, Databricks, or Snowflake are also relevant.

• Proven ability to solve issues related to data preparation, model execution, and infrastructure, addressing challenges from messy input files to slow model performance.

• Strong analytical skills for assessing data and outputs, including recognizing which issues warrant halting a run.

• Eagerness to learn and operate within the existing R-based production environment.

• A product engineering mindset that effectively balances reliability, usability, and delivery requirements.

• Capability to lead a small, skilled data science team through practical technical guidance and complex delivery challenges.

• Comfortable engaging in client calls to articulate technical methods and trade-offs, discuss data needs, and comprehend clients’ technology stacks and infrastructure.

• A genuine passion for developing AI-assisted workflows, quickly learning new tools, and critically assessing their outputs.

• Preferred: Experience in building and evaluating AI-assisted workflows for data preparation and modeling, including LLM or agent-based systems.

• Preferred: Experience with production R, encompassing packaging, dependency management, containers, or C++ integration via Rcpp.

• Preferred: Background in statistical modeling, particularly familiarity with CLV or BTYD models.

• Preferred: Experience in deploying data or modeling workflows in client-managed environments, such as Databricks, Snowflake, or Spark.

• Preferred: Familiarity with infrastructure as code practices, such as Terraform or similar, along with CI/CD experience.

🏝️ Benefits

• Opportunity to lead innovative projects in a collaborative environment.

• Access to cutting-edge tools and technologies to enhance your skills.

• Competitive salary and flexible work arrangements.